AI Engineer

This is a fully remote position, open to applicants in United Kingdom.

📋 Description

• Design, develop, train, and deploy machine learning and AI models, encompassing predictive analytics, natural language processing (NLP), computer vision, and Generative AI solutions, to bolster client missions and achieve business outcomes.

• Create scalable, reusable AI products, accelerators, and solution components that can be utilized across various client engagements, enhancing delivery efficiency and consistency.

• Develop and integrate Generative AI and large language model (LLM) capabilities utilizing platforms like Azure AI Foundry and Azure OpenAI, ensuring that solutions are secure, responsible, and aligned with client needs.

• Implement and continuously refine MLOps practices, including model deployment, monitoring, governance, retraining, and lifecycle management, to guarantee reliable performance of AI systems in production.

• Engineer features, datasets, and data pipelines from both structured and unstructured data sources, collaborating closely with data engineers and analysts to provide actionable insights.

• Apply responsible AI principles to ensure fairness, transparency, explainability, security, and compliance throughout the lifecycle of AI solutions.

• Work in partnership with consultants, technical specialists, and client stakeholders to comprehend operational challenges and convert them into effective, value-driven AI solutions.

• Contribute to technical proposals, demonstrations, proof-of-concepts, and thought leadership initiatives showcasing Envitia's AI capabilities to support business growth.

• Stay abreast of emerging AI technologies, frameworks, and best practices, identifying opportunities to enhance Envitia's capabilities and client offerings.

• Promote knowledge sharing, mentoring, and capability development within the AI team, the broader Consulting function, and the AI Community of Practice.

⛳️ Requirements

• Proficient in Python programming with hands-on experience in core ML/AI libraries (such as scikit-learn, TensorFlow, PyTorch).

• Practical experience in developing, training, and evaluating machine learning, NLP, and predictive models.

• Experience with deploying AI/ML in the cloud, especially on Microsoft Azure (Azure AI/ML, Azure AI Foundry / Azure OpenAI).

• Familiarity with Generative AI / large language models and prompt engineering as applied to real-world use cases.

• Understanding of MLOps practices related to model deployment, monitoring, and lifecycle management.

• Strong data engineering skills across structured and unstructured data, along with knowledge of responsible AI, data governance, and security; excellent communication skills for both technical and non-technical audiences.

• Experience in a consulting or client-facing delivery environment (preferred).

• Exposure to data visualization tools (Power BI, Tableau) and rapid front-end prototyping (Streamlit, Flask, Django, Figma) (preferred).

• Experience working with geospatial data (preferred).

• Experience delivering services within the UK public sector, Defence, or National Security (preferred).

• Familiarity with Databricks and/or Snowflake (preferred).

• A relevant degree (Computer Science, Data Science, AI/ML, or a related field) or equivalent practical experience (preferred).

🏝️ Benefits

• Annual Leave: 25 days plus your birthday off, with the option to buy or sell up to five additional days.

• Private Healthcare: Comprehensive coverage with additional options available for family members.

• Training & Skills Development: Continuous learning opportunities to facilitate career advancement.

• Fitness Reimbursement: Support for gym memberships or fitness-related expenses.

• Life Assurance: Extensive life insurance coverage for your peace of mind.

• Pension Contribution: Competitive options to assist in planning for a secure financial future.

• Perkbox Subscription: Discounts on a wide array of products and services.

• Flexible Work Arrangements: Designed to promote work-life balance and accommodate personal commitments.

• Internal Reward Schemes: Recognition initiatives to celebrate your contributions and achievements.

• Community Engagement & Volunteering: Opportunities to support meaningful causes through company-sponsored programs.